Workflow86

workflow86

What Are the Top Startups in Oceania?

In today's tech world with fierce competition and tight deadlines, it is useful to explore new and exciting tools to improve the workflow. Open-source tools are there to help; with some significant advantages over other tools - they're customizable, offer more control, and are community-driven. I decided to handpick 9 powerful open-source projects that will enhance your cloud workflow, project management, user feedback, automation, and more. Whether you are a beginner or a seasoned developer there should be something for everyone to elevate your toolkit and inspire your next big project. Let’s dive in and hopefully, you will find some tools that you can use in the future! 1. StackQL – Manage cloud services with SQL StackQL offers a revolutionary approach to deploy, query, and interact with cloud services and resources using Structured query language (SQL). That means you no longer need to learn different APIs for each provider. StackQL parses your SQL statements and transpiles them into API requests that all your favorite major cloud providers would understand. Some of the best features include: SQL-based querying: unified SQL semantics for various cloud providers lets you save time and manage cloud services more efficiently.


Multi-cloud support: manage Google Cloud, AWS, Azure, Digital Ocean, etc. resources all from a single interface.


Several usage modes: use StackQL via the interactive REPL shell, via the command line utility, or execute StackQL statements in an input file (IQL file).


Powerful operations: perform live queries against cloud resources, make configuration changes, manage cloud infrastructure, and more.


Available for various OS: available to download for Windows, MacOS, and Linux. Ready to reduce setup times and simplify your cloud configurations? Try StackQL yourself and explore all the awesome features it comes with! ⭐ Star StackQL on GitHub: github.com/stackql/stackql 🌎 Website: stackql.io Thanks to the StackQL team for sponsoring this article. 2. Flagsmith – Feature flag management Flagsmith is an open-source feature flag management tool. You can use hosted API, deploy to your private cloud, or run as on-premise software. It enables gradual feature rollouts for safer deployments and easier A/B testing, reducing the risk of bugs and ensuring faster iteration cycles. 👨‍💻 GitHub Repository: https://github.com/Flagsmith/flagsmith 🌎 Website: flagsmith.com 3. Formbricks – User feedback and analytics Formbricks is an open-source tool for collecting user feedback and form analytics. It helps devs understand user behavior, allowing them to improve performance, reduce friction, and enhance the overall UX. 👨‍💻 GitHub Repository: https://github.com/formbricks/formbricks 🌎 Website: formbricks.com 4. Dub – URL shortener with analytics Dub is an open-source URL shortener with built-in analytics. It simplifies link management for websites, marketing, and projects. By allowing developers to manage and analyze shortened URLs, Dub streamlines project workflows, making link tracking and data gathering much easier. 👨‍💻 GitHub Repository: https://github.com/dubinc/dub 🌎 Website: dub.co 5. AppFlowy – Project & notes management AppFlowy is an open-source, privacy-focused alternative to Notion. It provides a flexible workspace for managing tasks, notes, and general knowledge. AppFlowy offers teams control over their data and customizations, allowing them to create a tailored workspace while benefiting from privacy and scalability. 👨‍💻 GitHub Repository: https://github.com/AppFlowy-IO/AppFlowy 🌎 Website: appflowy.io 6. APITable – Visual database for collaborative apps APITable combines the ease of spreadsheets with the power of databases. It helps teams collaborate on data-driven projects with visual and interactive tables. APITable simplifies data management and collaboration, allowing developers to organize and automate workflows with minimal setup and technical knowledge. 👨‍💻 GitHub Repository: https://github.com/apitable/apitable 🌎 Website: aitable.ai 7. Flowise – Build LLM workflows with flowcharts Flowise is an open-source visual tool that simplifies building workflows for large language models (LLMs). It’s designed to integrate AI with apps easily. Flowise allows developers to visually manage complex LLM workflows, speeding up the integration of AI into their applications without deep coding knowledge. 👨‍💻 GitHub Repository: https://github.com/FlowiseAI/Flowise 🌎 Website: flowiseai.com 8. Jan – Use AI with full control and privacy Jan is an open-source tool; a ChatGPT alternative that runs 100% offline on your device but with more control, flexibility, and no privacy concerns. Jan enhances productivity by allowing you to ask questions, brainstorm, and learn from the AI running on your device to be more productive. 👨‍💻 GitHub Repository: https://github.com/janhq/jan 🌎 Website: jan.ai 9. Docsify – Documentation site generator Docsify is an open-source documentation site generator that creates beautiful, responsive docs from markdown files. It simplifies the process of generating documentation, making it easy for developers to maintain and update their docs without complex builds. 👨‍💻 GitHub Repository: https://github.com/docsifyjs/docsify 🌎 Website: docsify.js.org Did you like the resources? Here is more 👇 Join 6000+ others to receive the best DEV resources, tools, productivity tips, and career growth advice I discover by subscribing to my newsletter! Also, connect with me on Twitter, LinkedIn, and GitHub! Writing has always been my passion and it gives me pleasure to help and inspire people. If you want to get featured or partner up, feel free to get in touch! Also, published here. In today's tech world with fierce competition and tight deadlines, it is useful to explore new and exciting tools to improve the workflow. Open-source tools are there to help; with some significant advantages over other tools - they're customizable, offer more control, and are community-driven. I decided to handpick 9 powerful open-source projects that will enhance your cloud workflow, project management, user feedback, automation, and more. Whether you are a beginner or a seasoned developer there should be something for everyone to elevate your toolkit and inspire your next big project. Let’s dive in and hopefully, you will find some tools that you can use in the future! 1. StackQL – Manage cloud services with SQL StackQL StackQL offers a revolutionary approach to deploy, query, and interact with cloud services and resources using Structured query language (SQL). That means you no longer need to learn different APIs for each provider. StackQL parses your SQL statements and transpiles them into API requests that all your favorite major cloud providers would understand. Some of the best features include: Some of the best features include: SQL-based querying: unified SQL semantics for various cloud providers lets you save time and manage cloud services more efficiently. Multi-cloud support: manage Google Cloud, AWS, Azure, Digital Ocean, etc. resources all from a single interface. Several usage modes: use StackQL via the interactive REPL shell, via the command line utility, or execute StackQL statements in an input file (IQL file). Powerful operations: perform live queries against cloud resources, make configuration changes, manage cloud infrastructure, and more. Available for various OS: available to download for Windows, MacOS, and Linux. SQL-based querying: unified SQL semantics for various cloud providers lets you save time and manage cloud services more efficiently. SQL-based querying : unified SQL semantics for various cloud providers lets you save time and manage cloud services more efficiently. SQL-based querying Multi-cloud support: manage Google Cloud, AWS, Azure, Digital Ocean, etc. resources all from a single interface. Multi-cloud support: manage Google Cloud, AWS, Azure, Digital Ocean, etc. resources all from a single interface. Multi-cloud support: Several usage modes: use StackQL via the interactive REPL shell, via the command line utility, or execute StackQL statements in an input file (IQL file). Several usage modes: use StackQL via the interactive REPL shell, via the command line utility, or execute StackQL statements in an input file (IQL file). Several usage modes: Powerful operations: perform live queries against cloud resources, make configuration changes, manage cloud infrastructure, and more. Powerful operations: perform live queries against cloud resources, make configuration changes, manage cloud infrastructure, and more. Powerful operations: Available for various OS: available to download for Windows, MacOS, and Linux. Available for various OS : available to download for Windows, MacOS, and Linux. Available for various OS Ready to reduce setup times and simplify your cloud configurations? Try StackQL yourself and explore all the awesome features it comes with! ⭐ Star StackQL on GitHub: github.com/stackql/stackql Star StackQL on GitHub: github.com/stackql/stackql github.com/stackql/stackql 🌎 Website: stackql.io 🌎 Website: stackql.io stackql.io Thanks to the StackQL team for sponsoring this article. 2. Flagsmith – Feature flag management Flagsmith Flagsmith is an open-source feature flag management tool. You can use hosted API, deploy to your private cloud, or run as on-premise software. It enables gradual feature rollouts for safer deployments and easier A/B testing, reducing the risk of bugs and ensuring faster iteration cycles. 👨‍💻 GitHub Repository: https://github.com/Flagsmith/flagsmith GitHub Repository: https://github.com/Flagsmith/flagsmith 🌎 Website: flagsmith.com 🌎 Website: flagsmith.com 3. Formbricks – User feedback and analytics Formbricks Formbricks is an open-source tool for collecting user feedback and form analytics. It helps devs understand user behavior, allowing them to improve performance, reduce friction, and enhance the overall UX. 👨‍💻 GitHub Repository: https://github.com/formbricks/formbricks GitHub Repository: https://github.com/formbricks/formbricks 🌎 Website: formbricks.com 🌎 Website: formbricks.com 4. Dub – URL shortener with analytics Dub Dub is an open-source URL shortener with built-in analytics. It simplifies link management for websites, marketing, and projects. By allowing developers to manage and analyze shortened URLs, Dub streamlines project workflows, making link tracking and data gathering much easier. 👨‍💻 GitHub Repository: https://github.com/dubinc/dub GitHub Repository: https://github.com/dubinc/dub 🌎 Website: dub.co 🌎 Website: dub.co 5. AppFlowy – Project & notes management AppFlowy AppFlowy is an open-source, privacy-focused alternative to Notion. It provides a flexible workspace for managing tasks, notes, and general knowledge. AppFlowy offers teams control over their data and customizations, allowing them to create a tailored workspace while benefiting from privacy and scalability. 👨‍💻 GitHub Repository: https://github.com/AppFlowy-IO/AppFlowy GitHub Repository: https://github.com/AppFlowy-IO/AppFlowy 🌎 Website: appflowy.io 🌎 Website: appflowy.io 6. APITable – Visual database for collaborative apps APITable APITable combines the ease of spreadsheets with the power of databases. It helps teams collaborate on data-driven projects with visual and interactive tables. APITable simplifies data management and collaboration, allowing developers to organize and automate workflows with minimal setup and technical knowledge. 👨‍💻 GitHub Repository: https://github.com/apitable/apitable GitHub Repository: https://github.com/apitable/apitable 🌎 Website: aitable.ai 🌎 Website: aitable.ai 7. Flowise – Build LLM workflows with flowcharts Flowise Flowise is an open-source visual tool that simplifies building workflows for large language models (LLMs). It’s designed to integrate AI with apps easily. Flowise allows developers to visually manage complex LLM workflows, speeding up the integration of AI into their applications without deep coding knowledge. 👨‍💻 GitHub Repository: https://github.com/FlowiseAI/Flowise GitHub Repository: https://github.com/FlowiseAI/Flowise 🌎 Website: flowiseai.com 🌎 Website: flowiseai.com 8. Jan – Use AI with full control and privacy Jan Jan is an open-source tool; a ChatGPT alternative that runs 100% offline on your device but with more control, flexibility, and no privacy concerns. Jan enhances productivity by allowing you to ask questions, brainstorm, and learn from the AI running on your device to be more productive. 👨‍💻 GitHub Repository: https://github.com/janhq/jan GitHub Repository: https://github.com/janhq/jan 🌎 Website: jan.ai 🌎 Website: jan.ai 9. Docsify – Documentation site generator Docsify Docsify is an open-source documentation site generator that creates beautiful, responsive docs from markdown files. It simplifies the process of generating documentation, making it easy for developers to maintain and update their docs without complex builds. 👨‍💻 GitHub Repository: https://github.com/docsifyjs/docsify GitHub Repository: https://github.com/docsifyjs/docsify 🌎 Website: docsify.js.org 🌎 Website: docsify.js.org Did you like the resources? Here is more 👇 Join 6000+ others to receive the best DEV resources, tools, productivity tips, and career growth advice I discover by subscribing to my newsletter ! my newsletter Also, connect with me on Twitter , LinkedIn , and GitHub ! Twitter LinkedIn GitHub Writing has always been my passion and it gives me pleasure to help and inspire people. If you want to get featured or partner up, feel free to get in touch ! get in touch Also, published here . here

9 Open Source Projects Every Developer Needs to Bookmark for Their Workflow

Optimizing workflows with AI has become a game-changer for me, especially when it comes to searching for information. For a while, I relied on the free version of Perplexity, but recently, I upgraded to Perplexity Pro. Meanwhile, as a longtime user of ChatGPT, I’ve also been exploring its new ChatGPT Search feature. In this article, I’ll share my experiences with both tools, compare their strengths and weaknesses, and help you decide which one might be the better fit for your needs. Perplexity I’d heard about Perplexity.ai many times, promised myself I’d try it, and eventually did, but it didn’t quite click. It’s hard to fully appreciate a tool until you use it regularly. I forgot about it until I got a test assignment for a job interview in a new field, requiring tons of research. Honestly, I’m not great at googling. But since I frequently use ChatGPT and have gotten pretty good at writing prompts, I thought of giving Perplexity another shot. This was before the release of ChatGPT Search, and at that point, I’d already maxed out what ChatGPT could offer. Perplexity turned out to be a lifesaver. It made long, tedious searches much quicker and was my first truly game-changing experience with AI search. At the time, I used the free version. Compared to browser searches, here’s what I found more convenient in AI search: Fewer distractions from ads: Most browsers put ads at the top, so you have to scroll past them just to get to the first actual search result. Even without the ads, the top links are often not very relevant, and there are still too many to sift through. This makes it easy to lose motivation to click beyond the first couple of pages. AI does all that for you, providing a list of sources you can explore further on your own.


Threaded searches with context: I loved how searches are organized into threads, preserving context. For my test assignment, since I was learning a new field from scratch, one question would lead to many others. It was convenient to continue and expand the search without starting over each time. If I remembered something later, I could easily return to a specific thread and pick up where I left off.


Helpful question suggestions: Each thread in Perplexity includes prompts for related questions, which makes navigating a new topic much easier.


Incognito mode: Like most browsers, Perplexity offers an incognito mode. I haven’t used it yet, but it’s a nice feature.


Language flexibility: If you write in a certain language, you’ll get sources in that language. This is a standard approach for browsers but not always convenient. For a while, I continued using the free version, but recently I switched to Pro. The free version uses the GPT-3.5 model, whereas the Pro plan grants access to the latest models: GPT-4 Omni, Claude-3 Sonnet/Opus, and Sonar Large 32k, so all the best features are integrated into your search. Of course, the Pro version offers better, smarter, and faster search. In addition to the features mentioned above, here’s what I found most useful: Broaden your search with images: Pro provides access to Playground V2.5, DALLE 3, and Stable Diffusion XL models that can expand your search. For example, I was recently researching fund flow modeling, and having visual examples was incredibly helpful.


Files, code, and more input options: You can upload unlimited files, code, pictures, etc. It’s really fast and much more convenient than doing this through a standard browser because it’s all in one space with seamless AI interaction. ChatGPT Search This feature was launched in October 2024 and is based on GPT-4o, specifically trained for search. It’s integrated into ChatGPT, allowing you to enable it with a Search button or simply ask ChatGPT to search the web. As I mentioned, I’ve been a long-time user of ChatGPT for several years, so I seamlessly integrated the search feature into my routine. Since free Perplexity uses GPT-3.5, all its features like AI search with no ads, no endless scrolling, and results organized into threads with helpful tips are available here as well. My favorite feature here is its accessibility, offering text-to-speech, and the ability to create queries via audio, and audio dialogs. Choose your fighter Search Quality Perplexity excels at finding information, while ChatGPT Search is better at explaining it. From a user perspective, I wouldn’t say I’ve encountered any critical issues with not finding something. It’s just a matter of different approaches. Perplexity provides more an overview of sources, whereas ChatGPT tends to give more explanation than summary. Generated Answers Without Sources Both tools provide sources for their answers, but sometimes the information might be generated without a reliable link. Even when a link is provided, the relevant information might not actually be there. It’s always better to double-check and read the sources yourself. Based on my experience, ChatGPT is more prone to generating unsupported content than Perplexity, but I’ve encountered this issue in both tools. Search Speed I didn’t notice a significant difference between the two in terms of speed. However, both are slower than a standard browser search. Chrome extensions Both tools offer Chrome extensions, and I tested both. The ChatGPT extension lets you use ChatGPT as your primary search engine, replacing, for example, Google. When you enter something in the search bar, it redirects you to ChatGPT, where your query is processed. Honestly, I wasn’t a fan. It’s slower than Google, and you can feel it. I still prefer a traditional search bar for quick lookups. Perplexity’s Chrome extension works differently. Instead of replacing your search engine, it opens a small window over the current page, allowing you to googling and query Perplexity simultaneously. I really loved this one, because it’s more useful for me. The drawback is that you can only enter one query at a time, and if you want to continue the conversation, it redirects you to a separate Perplexity tab. Unique Features Since both tools use GPT models, they share many great features. Perplexity Pro stands out with its use of multiple models and built-in illustrations. On the other hand, I really appreciate ChatGPT’s accessibility and seamless integration into its apps, which I use for more than just search. Bonus: Hangman game test I saw a funny tweet claiming ChatGPT can’t play Hangman. Turns out, neither can Perplexity Pro, even with all its models. Final Take: Which Works Best for What To start with, I’m a fan of AI search. Usually, it takes longer than quick googling, so here’s how I see it: if I need a super quick answer from the first link, I’ll use a standard browser search. But if I need to find more information or conduct deeper research, AI search is the way to go. It’s the best method to uncover valuable insights more efficiently. As for ChatGPT Search and Perplexity, in my experience, they solve different problems. ChatGPT Search perfectly extends ChatGPT’s capabilities, given that ChatGPT’s knowledge base only goes up to the year 2021. It’s perfect for studying and gaining insights using up-to-date web information. Perplexity, on the other hand, is better for finding something more thoroughly. It takes more from browser search, like incognito pages, and its approach to work with your prompts. It is about searching for information first and explaining second, in contrast to ChatGPT Search. For me: Need to find something? Perplexity.
Need to understand something? ChatGPT + Search. They complement each other perfectly in work. Optimizing workflows with AI has become a game-changer for me, especially when it comes to searching for information. For a while, I relied on the free version of Perplexity , but recently, I upgraded to Perplexity Pro . Meanwhile, as a longtime user of ChatGPT , I’ve also been exploring its new ChatGPT Search feature. In this article, I’ll share my experiences with both tools, compare their strengths and weaknesses, and help you decide which one might be the better fit for your needs. Perplexity Perplexity Pro ChatGPT ChatGPT Search Perplexity I’d heard about Perplexity.ai many times, promised myself I’d try it, and eventually did, but it didn’t quite click. It’s hard to fully appreciate a tool until you use it regularly. I forgot about it until I got a test assignment for a job interview in a new field, requiring tons of research. Honestly, I’m not great at googling. But since I frequently use ChatGPT and have gotten pretty good at writing prompts, I thought of giving Perplexity another shot. This was before the release of ChatGPT Search, and at that point, I’d already maxed out what ChatGPT could offer. Perplexity turned out to be a lifesaver. It made long, tedious searches much quicker and was my first truly game-changing experience with AI search. Perplexity.ai At the time, I used the free version. Compared to browser searches, here’s what I found more convenient in AI search: Fewer distractions from ads: Most browsers put ads at the top, so you have to scroll past them just to get to the first actual search result. Even without the ads, the top links are often not very relevant, and there are still too many to sift through. This makes it easy to lose motivation to click beyond the first couple of pages. AI does all that for you, providing a list of sources you can explore further on your own. Threaded searches with context: I loved how searches are organized into threads, preserving context. For my test assignment, since I was learning a new field from scratch, one question would lead to many others. It was convenient to continue and expand the search without starting over each time. If I remembered something later, I could easily return to a specific thread and pick up where I left off. Helpful question suggestions: Each thread in Perplexity includes prompts for related questions, which makes navigating a new topic much easier. Incognito mode: Like most browsers, Perplexity offers an incognito mode. I haven’t used it yet, but it’s a nice feature. Language flexibility: If you write in a certain language, you’ll get sources in that language. This is a standard approach for browsers but not always convenient. Fewer distractions from ads: Most browsers put ads at the top, so you have to scroll past them just to get to the first actual search result. Even without the ads, the top links are often not very relevant, and there are still too many to sift through. This makes it easy to lose motivation to click beyond the first couple of pages. AI does all that for you, providing a list of sources you can explore further on your own. Fewer distractions from ads: Most browsers put ads at the top, so you have to scroll past them just to get to the first actual search result. Even without the ads, the top links are often not very relevant, and there are still too many to sift through. This makes it easy to lose motivation to click beyond the first couple of pages. AI does all that for you, providing a list of sources you can explore further on your own. Fewer distractions from ads: Threaded searches with context: I loved how searches are organized into threads, preserving context. For my test assignment, since I was learning a new field from scratch, one question would lead to many others. It was convenient to continue and expand the search without starting over each time. If I remembered something later, I could easily return to a specific thread and pick up where I left off. Threaded searches with context: I loved how searches are organized into threads, preserving context. For my test assignment, since I was learning a new field from scratch, one question would lead to many others. It was convenient to continue and expand the search without starting over each time. If I remembered something later, I could easily return to a specific thread and pick up where I left off. Threaded searches with context: Helpful question suggestions: Each thread in Perplexity includes prompts for related questions, which makes navigating a new topic much easier. Helpful question suggestions: Each thread in Perplexity includes prompts for related questions, which makes navigating a new topic much easier. Helpful question suggestions: Incognito mode: Like most browsers, Perplexity offers an incognito mode. I haven’t used it yet, but it’s a nice feature. Incognito mode: Like most browsers, Perplexity offers an incognito mode. I haven’t used it yet, but it’s a nice feature. Incognito mode: Language flexibility: If you write in a certain language, you’ll get sources in that language. This is a standard approach for browsers but not always convenient. Language flexibility: If you write in a certain language, you’ll get sources in that language. This is a standard approach for browsers but not always convenient. Language flexibility: For a while, I continued using the free version, but recently I switched to Pro . The free version uses the GPT-3.5 model, whereas the Pro plan grants access to the latest models: GPT-4 Omni, Claude-3 Sonnet/Opus, and Sonar Large 32k, so all the best features are integrated into your search. Of course, the Pro version offers better, smarter, and faster search. Pro In addition to the features mentioned above, here’s what I found most useful: In addition to the features mentioned above, here’s what I found most useful: Broaden your search with images: Pro provides access to Playground V2.5, DALLE 3, and Stable Diffusion XL models that can expand your search. For example, I was recently researching fund flow modeling, and having visual examples was incredibly helpful. Files, code, and more input options: You can upload unlimited files, code, pictures, etc. It’s really fast and much more convenient than doing this through a standard browser because it’s all in one space with seamless AI interaction. Broaden your search with images: Pro provides access to Playground V2.5, DALLE 3, and Stable Diffusion XL models that can expand your search. For example, I was recently researching fund flow modeling, and having visual examples was incredibly helpful. Broaden your search with images: Pro provides access to Playground V2.5, DALLE 3, and Stable Diffusion XL models that can expand your search. For example, I was recently researching fund flow modeling, and having visual examples was incredibly helpful. Broaden your search with images: Files, code, and more input options: You can upload unlimited files, code, pictures, etc. It’s really fast and much more convenient than doing this through a standard browser because it’s all in one space with seamless AI interaction. Files, code, and more input options: You can upload unlimited files, code, pictures, etc. It’s really fast and much more convenient than doing this through a standard browser because it’s all in one space with seamless AI interaction. Files, code, and more input options: ChatGPT Search ChatGPT Search This feature was launched in October 2024 and is based on GPT-4o, specifically trained for search. It’s integrated into ChatGPT , allowing you to enable it with a Search button or simply ask ChatGPT to search the web. ChatGPT As I mentioned, I’ve been a long-time user of ChatGPT for several years, so I seamlessly integrated the search feature into my routine. Since free Perplexity uses GPT-3.5, all its features like AI search with no ads, no endless scrolling, and results organized into threads with helpful tips are available here as well. My favorite feature here is its accessibility, offering text-to-speech, and the ability to create queries via audio, and audio dialogs. Choose your fighter Search Quality Search Quality Search Quality Search Quality Perplexity excels at finding information, while ChatGPT Search is better at explaining it. From a user perspective, I wouldn’t say I’ve encountered any critical issues with not finding something. It’s just a matter of different approaches. Perplexity provides more an overview of sources, whereas ChatGPT tends to give more explanation than summary. overview explanation Generated Answers Without Sources Generated Answers Without Sources Generated Answers Without Sources Generated Answers Without Sources Both tools provide sources for their answers, but sometimes the information might be generated without a reliable link. Even when a link is provided, the relevant information might not actually be there. It’s always better to double-check and read the sources yourself. Based on my experience, ChatGPT is more prone to generating unsupported content than Perplexity, but I’ve encountered this issue in both tools. Search Speed Search Speed Search Speed Search Speed I didn’t notice a significant difference between the two in terms of speed. However, both are slower than a standard browser search. Chrome extensions Chrome extensions Chrome extensions Chrome extensions Both tools offer Chrome extensions, and I tested both. The ChatGPT extension lets you use ChatGPT as your primary search engine, replacing, for example, Google. When you enter something in the search bar, it redirects you to ChatGPT, where your query is processed. Honestly, I wasn’t a fan. It’s slower than Google, and you can feel it. I still prefer a traditional search bar for quick lookups. Perplexity’s Chrome extension works differently. Instead of replacing your search engine, it opens a small window over the current page, allowing you to googling and query Perplexity simultaneously. I really loved this one, because it’s more useful for me. The drawback is that you can only enter one query at a time, and if you want to continue the conversation, it redirects you to a separate Perplexity tab. Unique Features Unique Features Unique Features Unique Features Since both tools use GPT models, they share many great features. Perplexity Pro stands out with its use of multiple models and built-in illustrations. On the other hand, I really appreciate ChatGPT’s accessibility and seamless integration into its apps, which I use for more than just search. Bonus: Hangman game test Bonus: Hangman game test Bonus: Hangman game test Bonus: Hangman game test I saw a funny tweet claiming ChatGPT can’t play Hangman. Turns out, neither can Perplexity Pro, even with all its models. Final Take: Which Works Best for What To start with, I’m a fan of AI search. Usually, it takes longer than quick googling, so here’s how I see it: if I need a super quick answer from the first link, I’ll use a standard browser search. But if I need to find more information or conduct deeper research, AI search is the way to go. It’s the best method to uncover valuable insights more efficiently. As for ChatGPT Search and Perplexity, in my experience, they solve different problems. ChatGPT Search perfectly extends ChatGPT’s capabilities, given that ChatGPT’s knowledge base only goes up to the year 2021. It’s perfect for studying and gaining insights using up-to-date web information. Perplexity, on the other hand, is better for finding something more thoroughly. It takes more from browser search, like incognito pages, and its approach to work with your prompts. It is about searching for information first and explaining second, in contrast to ChatGPT Search. For me: For me: Need to find something? Perplexity. Need to understand something? ChatGPT + Search. Need to find something? Perplexity. Need to find something? Need to understand something? ChatGPT + Search. Need to understand something? They complement each other perfectly in work.

Perplexity Pro vs. ChatGPT Search: Which AI Tool is Best Fits Your Workflow Needs?

Perplexity супраць пошуку ChatGPT: які інструмент AI лепш за ўсё адпавядае вашым патрэбам працоўнага працэсу?

Perplexity срещу ChatGPT Search: Кой AI инструмент отговаря най-добре на вашите нужди от работен процес?

Perplexity vs. Búsqueda en ChatGPT: ¿Qué herramienta de IA se adapta mejor a sus necesidades de flujo de trabajo?

Շփոթմունքն ընդդեմ ChatGPT որոնման. Ո՞ր AI գործիքն է լավագույնս համապատասխանում ձեր աշխատանքային հոսքի կարիքներին:

Perplexity と ChatGPT Search: どちらの AI ツールがワークフローのニーズに最適ですか?

ភាពច្របូកច្របល់ធៀបនឹងការស្វែងរក ChatGPT៖ តើឧបករណ៍ AI មួយណាដែលសាកសមបំផុតនឹងតម្រូវការលំហូរការងាររបស់អ្នក?

Perplexity vs. ChatGPT paieška: kuris AI įrankis geriausiai atitinka jūsų darbo eigos poreikius?

Fikarohana ChatGPT: Inona no fitaovana AI mifanaraka amin'ny filanao?

Збунетост наспроти Пребарување ChatGPT: која алатка за вештачка интелигенција најдобро одговара на вашите потреби на работниот тек?

Urujijo na ChatGPT Gushakisha: Niki Gikoresho cya AI gihuye neza nakazi kawe gakenewe?

குழப்பம் மற்றும் ChatGPT தேடல்: எந்த AI கருவி உங்கள் பணிப்பாய்வு தேவைகளுக்கு மிகவும் பொருத்தமானது?

Perplexity กับ ChatGPT Search: เครื่องมือ AI ตัวใดที่เหมาะกับความต้องการเวิร์กโฟลว์ของคุณที่สุด

The Building Blocks of UI/UX: How Atomic Design Transforms Your Workflow

You may want to ask, "What is Coze?" and "Why should I care?" Well, as it is stated on their official website, Coze is a next-generation AI Agent building platform. Coze enables users with all levels of programming (and no code) experience to create various chatbots and deploy them across social platforms and messaging apps like Discord, Telegram, LINE and Slack. Why should I care? Coze has been proven to be very helpful and easy to use. Here is why: - Coze allows you (as a user) to use GPT-4 Turbo (128K) for free. We have seen different techniques, such as RAG and GPT4V. Usually, these require a lot more work to do locally. There is software to install, many things to configure, and many errors to solve. But with Coze, all of these can be done easily, even with no code experience. - As a platform, other bots can be used (as Multi-agent) via their Agent (Bot) Store. Besides, the bot can also be deployed on many other social platforms such as Discord and Telegram.   Imagine sharing your own AI bots with your friends. Isn't it cool? To crown it all, before I show you how to build a GPT4 Workflow/ Chatbot with Coze, the Coze platform offers a Coze Assistant bot, which already has a strong ability to help you create any bot (even with no code experience) and can call another user-created bot by simply typing '@'. How to Build GPT4 Workflow/Chatbot With Coze Step 1 Simply click the '+ Create bot' button on the top left. Give it a name and description of your bot. Click the 'Generate' button below, and the profile picture can be generated easily using Coze AI. Step 2 Then is the most interesting part; a workspace where you can design everything of your bot, in creation. Have you seen 'GPT-4 (8K)' on top? Look up. Here, you can switch the model and change its parameters, such as temperature. Have you heard the debate about whether ChatGPT gets stupid? It's funny right‽ Many said that it's because of the change in ChatGPT temperature. Here you are in control of the temperature of our own bot. Step 3 To begin, write down the persona and prompt of the bot, like 'You are a good translator, and you will translate chats according to the user's chats.' We can even use AI to optimize the translation prompts.  The optimized prompt looks more professional, right? After this, we can change its ability. For example, if we want to gain the ability to gather information from a picture uploaded by the user, we can add the GPT4V plugin in the menu that pops up after we click '+' on the left of 'plugin'. Step 4 A more interesting thing is that we can use our own knowledge base here. First, we need to create a knowledge base on the Coze platform. We can upload PDF documents, Notion links, and many other things here. We can do segmentation in either an automated way or a custom way. Later, we will still be able to edit the segmentation. After this, we add the knowledge base to the bot's workspace. We can choose a call method and set other parameters. If we choose 'on Demand Call', we must add 'recallKnowledge' in the prompt. In addition We can change its opening questions/greetings to reflect its appearance and experience. We can even choose the bot's voice to read its output automatically. Step 5 And finally, click the 'publish' button on the top right corner, and then we can deploy it across various platforms such as Coze's own bot store, Telegram configuring the bot with tokens obtained from BotFather in Telegram, and setting up the bot's interactions and responses. It's also super easy. Note: This does not mention other functions, such as Multi-agent, Skills, and Memory. Coze is really easy to use. You may want to ask, "What is Coze?" and "Why should I care?" Well, as it is stated on their official website , Coze is a next-generation AI Agent building platform. "What is Coze?" "What is Coze?" "Why should I care?" "Why should I care?" official website Coze enables users with all levels of programming (and no code) experience to create various chatbots and deploy them across social platforms and messaging apps like Discord, Telegram, LINE and Slack. Coze enables users with all levels of programming (and no code) experience to create various chatbots and deploy them across social platforms and messaging apps like Discord, Telegram, LINE and Slack. (and no code) Why should I care? Why should I care? Coze has been proven to be very helpful and easy to use. Here is why: - Coze allows you (as a user) to use GPT-4 Turbo (128K) for free. We have seen different techniques, such as RAG and GPT4V. Usually, these require a lot more work to do locally. There is software to install, many things to configure, and many errors to solve. But with Coze, all of these can be done easily, even with no code experience. (as a user) - As a platform, other bots can be used (as Multi-agent) via their Agent (Bot) Store. Besides, the bot can also be deployed on many other social platforms such as Discord and Telegram. Imagine sharing your own AI bots with your friends. Isn't it cool? (as Multi-agent) (Bot) Imagine sharing your own AI bots with your friends. Isn't it cool? Imagine sharing your own AI bots with your friends. Isn't it cool? To crown it all, before I show you how to build a GPT4 Workflow/ Chatbot with Coze, the Coze platform offers a Coze Assistant bot, which already has a strong ability to help you create any bot (even with no code experience) and can call another user-created bot by simply typing '@'. how to build a GPT4 Workflow/ Chatbot with Coze, how to build a GPT4 Workflow/ Chatbot with Coze, How to Build GPT4 Workflow/Chatbot With Coze Step 1 Step 1 Simply click the '+ Create bot' button on the top left. Give it a name and description of your bot. Click the 'Generate' button below, and the profile picture can be generated easily using Coze AI. '+ Create bot' '+ Create bot' 'Generate' 'Generate' Step 2 Step 2 Then is the most interesting part; a workspace where you can design everything of your bot, in creation. Have you seen 'GPT-4 (8K)' on top? Look up. Here, you can switch the model and change its parameters, such as temperature. 'GPT-4 (8K)' 'GPT-4 (8K)' Have you heard the debate about whether ChatGPT gets stupid? It's funny right‽ Many said that it's because of the change in ChatGPT temperature. Have you heard the debate about whether ChatGPT gets stupid? It's funny right‽ Many said that it's because of the change in ChatGPT temperature. Have you heard the debate about whether ChatGPT gets stupid? It's funny right‽ Many said that it's because of the change in ChatGPT temperature. Here you are in control of the temperature of our own bot. Step 3 Step 3 To begin, write down the persona and prompt of the bot, like 'You are a good translator, and you will translate chats according to the user's chats.' We can even use AI to optimize the translation prompts. The optimized prompt looks more professional, right? 'You are a good translator, and you will translate chats according to the user's chats.' 'You are a good translator, and you will translate chats according to the user's chats.' After this, we can change its ability. For example, if we want to gain the ability to gather information from a picture uploaded by the user, we can add the GPT4V plugin in the menu that pops up after we click '+' on the left of 'plugin' . '+' '+' 'plugin' 'plugin' Step 4 Step 4 A more interesting thing is that we can use our own knowledge base here. First, we need to create a knowledge base on the Coze platform. We can upload PDF documents, Notion links, and many other things here. We can do segmentation in either an automated way or a custom way. Later, we will still be able to edit the segmentation. After this, we add the knowledge base to the bot's workspace. We can do segmentation in either an automated way or a custom way. Later, we will still be able to edit the segmentation. After this, we add the knowledge base to the bot's workspace. We can choose a call method and set other parameters. If we choose 'on Demand Call' , we must add 'recallKnowledge' in the prompt. 'on Demand Call' 'on Demand Call' 'recallKnowledge' 'recallKnowledge' In addition In addition We can change its opening questions/greetings to reflect its appearance and experience. We can even choose the bot's voice to read its output automatically. Step 5 Step 5 And finally, click the 'publish' button on the top right corner, and then we can deploy it across various platforms such as Coze's own bot store, Telegram configuring the bot with tokens obtained from BotFather in Telegram , and setting up the bot's interactions and responses. It's also super easy. 'publish' 'publish' Telegram configuring the bot with tokens obtained from BotFather in Telegram Note: This does not mention other functions, such as Multi-agent, Skills, and Memory. Coze is really easy to use. Note:

Design and Deploy AI Chatbot Using Coze: How to Build a GPT4 Workflow/Chatbot for Free

I've been thinking about starting a new project using my go-to tech: Clojure. For me, it's the best tool around, and I’m always surprised that more people don’t see its potential. It’s a fantastic multi-purpose language design to build solid software, so I asked myself: What’s a good fit for it where I feel confident building something meaningful in my spare time? After some tinkering, I come up with this idea: A workflow automation tool. Think Zapier, but designed specifically for small and medium-sized businesses that need reliable and observable workflows. I believe Clojure’s strengths—its "everything is a map" data model and its powerful concurrency support—make it the perfect language for building robust API integrations. Why Build Another Workflow Tool? There are plenty of workflow automation tools like Zapier that offer a huge range of integrations. I can't challenge these platforms by being cheaper or offering more integrations. So, I started thinking: Why don’t I use these tools more often in my day-to-day work? I think it’s because of reliability, observability, and missing collaboration features. These platforms often feel like black boxes—when something goes wrong, it's hard to know why. Collaboration is often an afterthought: you need the business++ plan and the UX for it has been shoved into the product — hard to use something like that if you're in an organization larger than a startup. Worse for me, workflows are not easily observable: you're left hoping everything works as expected. In today’s world, there is no reason to guess whether your software is functioning. With the right tech, you can observe and ensure that everything works as expected. Building Software That “Just Works” I’m a big believer in building software that delivers value from day one. No overselling. No bugs lurking beneath the surface. Too many SaaS promise a lot but deliver a half-baked experience — as soon as you get out of the main use case of the tool, you have to contact the support to figure out what is going on. Nobody wants to spend time on a half-bake tool selling you promises. Users want value now, not after your next fundraising. My Initial Target I’m focusing on the basics: Create and edit workflows: The UX to configure the tool.
View workflow execution: View what works and what does not
Webhook integration: The basic block to build on top off
User roles and permissions: Enable teams to work together seamlessly
Export and edit workflows programmatically: Building block that allows integration to developer tools
Workflow status via API: Clear visibility into the state of every workflow.
On-demand pricing: Pay for what you use, when you use it. Once these core functionalities are in place, I’ll start adding more integrations—things like email, AWS APIs, tools for deployment, Notion (I use it a lot), Slack, human interaction workflows, and Google Workspace. Over time, I’ll figure out what other integrations make sense for users who share my vision of a workflow platform. Adding LLM support seems obvious in today’s market. Every company now needs to integrate with LLMs, managing things like throttling, token usage, and cost monitoring. I see real value in handling that complexity for users. Of course, I could be wrong—maybe companies will prefer to build their own LLM integrations. That reminds me of the beginning of the mobile apps business, I thought building mobile apps would be a flop because companies would have to maintain applications for search platforms and still do a responsive website to convince users to install their application. I was dead wrong, and now most companies maintain two mobile applications and at least one website, and eventually two when they have a website for mobile. The Challenge of Selling How will I market this project? Honestly, I’m not sure yet. My initial plan is to create something useful for myself that’s solid enough for others to use. Whether I manage to find users is still a big question mark, but I know I need to figure it out and articulate my value proposition clearly. Why I Will Succeed I’m confident in my ability to build this. I know how to leverage infrastructure to create something that’s both solid and scalable. With Clojure’s strengths and my experience, I believe I can deliver something valuable. Why I Could Fail Marketing and sales: This is my weakest area. I have limited experience, and finding the first users will be tricky. I also don’t enjoy platforms like Twitter, and this kind of social website with a tidbit of knowledge and a lot of noise. I prefer long-form content, but it’s harder to reach people that way and build an audience. I need to not underestimate the issue.
Market misjudgment: It’s possible that the workflow automation market won’t take off the way I expect. Companies will keep building integration after integration and discover over time that it is a costly handover to build and *maintain (*emphasis on maintaining as software estimation only accounts for the cost of building things and not on the cost of observing, debugging, upgrading, interconnecting, …)
Time constraints: Balancing family, a day job and other interests means I might not be able to dedicate as much time to this project as I’d like. Why This Will Make Me Happy Ultimately, it’s about the journey. This project will push me out of my comfort zone and challenge me to learn new things, not just in my area of expertise, but across the full software lifecycle. I’m excited to tackle the problems I’m less familiar with and grow from these experiences, regardless of the final outcome. I've been thinking about starting a new project using my go-to tech: Clojure. For me, it's the best tool around, and I’m always surprised that more people don’t see its potential. It’s a fantastic multi-purpose language design to build solid software, so I asked myself: What’s a good fit for it where I feel confident building something meaningful in my spare time? What’s a good fit for it where I feel confident building something meaningful in my spare time? After some tinkering, I come up with this idea: A workflow automation tool. Think Zapier, but designed specifically for small and medium-sized businesses that need reliable and observable workflows. I believe Clojure’s strengths—its "everything is a map" data model and its powerful concurrency support—make it the perfect language for building robust API integrations. Why Build Another Workflow Tool? There are plenty of workflow automation tools like Zapier that offer a huge range of integrations. I can't challenge these platforms by being cheaper or offering more integrations. So, I started thinking: Why don’t I use these tools more often in my day-to-day work? Why don’t I use these tools more often in my day-to-day work? I think it’s because of reliability, observability, and missing collaboration features. These platforms often feel like black boxes—when something goes wrong, it's hard to know why. Collaboration is often an afterthought: you need the business++ plan and the UX for it has been shoved into the product — hard to use something like that if you're in an organization larger than a startup. Worse for me, workflows are not easily observable: you're left hoping everything works as expected. In today’s world, there is no reason to guess whether your software is functioning. With the right tech, you can observe and ensure that everything works as expected. Building Software That “Just Works” I’m a big believer in building software that delivers value from day one. No overselling. No bugs lurking beneath the surface. Too many SaaS promise a lot but deliver a half-baked experience — as soon as you get out of the main use case of the tool, you have to contact the support to figure out what is going on. Nobody wants to spend time on a half-bake tool selling you promises. Users want value now, not after your next fundraising. My Initial Target I’m focusing on the basics: Create and edit workflows: The UX to configure the tool. View workflow execution: View what works and what does not Webhook integration: The basic block to build on top off User roles and permissions: Enable teams to work together seamlessly Export and edit workflows programmatically: Building block that allows integration to developer tools Workflow status via API: Clear visibility into the state of every workflow. On-demand pricing: Pay for what you use, when you use it. Create and edit workflows : The UX to configure the tool. Create and edit workflows View workflow execution: View what works and what does not View workflow execution: Webhook integration : The basic block to build on top off Webhook integration User roles and permissions : Enable teams to work together seamlessly User roles and permissions Export and edit workflows programmatically : Building block that allows integration to developer tools Export and edit workflows programmatically Workflow status via API : Clear visibility into the state of every workflow. Workflow status via API On-demand pricing : Pay for what you use, when you use it. On-demand pricing Once these core functionalities are in place, I’ll start adding more integrations—things like email, AWS APIs, tools for deployment, Notion (I use it a lot), Slack, human interaction workflows, and Google Workspace. Over time, I’ll figure out what other integrations make sense for users who share my vision of a workflow platform. Adding LLM support seems obvious in today’s market. Every company now needs to integrate with LLMs, managing things like throttling, token usage, and cost monitoring. I see real value in handling that complexity for users. Of course, I could be wrong—maybe companies will prefer to build their own LLM integrations. That reminds me of the beginning of the mobile apps business, I thought building mobile apps would be a flop because companies would have to maintain applications for search platforms and still do a responsive website to convince users to install their application. I was dead wrong, and now most companies maintain two mobile applications and at least one website, and eventually two when they have a website for mobile. The Challenge of Selling How will I market this project? Honestly, I’m not sure yet. My initial plan is to create something useful for myself that’s solid enough for others to use. Whether I manage to find users is still a big question mark, but I know I need to figure it out and articulate my value proposition clearly. Why I Will Succeed I’m confident in my ability to build this. I know how to leverage infrastructure to create something that’s both solid and scalable. With Clojure’s strengths and my experience, I believe I can deliver something valuable. Why I Could Fail Marketing and sales: This is my weakest area. I have limited experience, and finding the first users will be tricky. I also don’t enjoy platforms like Twitter, and this kind of social website with a tidbit of knowledge and a lot of noise. I prefer long-form content, but it’s harder to reach people that way and build an audience. I need to not underestimate the issue. Market misjudgment: It’s possible that the workflow automation market won’t take off the way I expect. Companies will keep building integration after integration and discover over time that it is a costly handover to build and *maintain (*emphasis on maintaining as software estimation only accounts for the cost of building things and not on the cost of observing, debugging, upgrading, interconnecting, …) Time constraints: Balancing family, a day job and other interests means I might not be able to dedicate as much time to this project as I’d like. Marketing and sales : This is my weakest area. I have limited experience, and finding the first users will be tricky. I also don’t enjoy platforms like Twitter, and this kind of social website with a tidbit of knowledge and a lot of noise. I prefer long-form content, but it’s harder to reach people that way and build an audience. I need to not underestimate the issue. Marketing and sales Market misjudgment : It’s possible that the workflow automation market won’t take off the way I expect. Companies will keep building integration after integration and discover over time that it is a costly handover to build and *maintain (*emphasis on maintaining as software estimation only accounts for the cost of building things and not on the cost of observing, debugging, upgrading, interconnecting, …) Market misjudgment Time constraints : Balancing family, a day job and other interests means I might not be able to dedicate as much time to this project as I’d like. Time constraints Why This Will Make Me Happy Ultimately, it’s about the journey. This project will push me out of my comfort zone and challenge me to learn new things, not just in my area of expertise, but across the full software lifecycle. I’m excited to tackle the problems I’m less familiar with and grow from these experiences, regardless of the final outcome.

Starting a New Side Project: Yet Another Workflow Tool

In-Depth Analysis of DolphinScheduler Task Scheduling, Splitting, and Execution Workflow

In December 2023, it was discovered that an NPM package commonly used by decentralized web applications (dApps) had been compromised. The package in question, @ledgerhq/connect-kit, is maintained by Ledger, a well-known and arguably the most trusted provider of secure hardware wallets. Ironic right? Well, not really, because the compromised package has nothing to do with the ledger's secure hardware wallets. However, the incident understandably raised concerns among users about the security of their assets, despite those assets being stored offline in hardware wallets. While the compromised package posed no immediate threat to Ledger's hardware devices, the situation sparked widespread discussion and speculation. The prevailing theory suggests that the compromise occurred due to a vulnerability in Ledger’s GitHub workflow. It is believed that an attacker exploited a GitHub pull request workflow to gain access to Ledger's NPM keys, enabling them to publish malicious code. The malicious update reportedly caused a secondary window to open when users attempted to connect their wallets. The Experiment The incident piqued my curiosity, prompting me to question whether GitHub workflows were inherently flawed or if there was more nuance to the exploit. To explore this, I conducted an experiment to see if I could replicate the vulnerability. Using an existing open-source repository, I attempted to recreate the exploit. During my testing, I discovered that: 1. A pull request can edit a workflow and the new workflow will run immediately after the pull request is made The screenshot below displays the contents of a pipeline.yml file from the repository I was working with. The pipeline is configured to trigger every push to the main branch, deploying the serverless application to AWS. I proceeded by creating a new branch within the repository and modifying the pipeline file. The updated configuration was set to trigger the workflow on every pull request, regardless of the branch. The screenshot below illustrates the modified state of the file. Along with these modifications, I added an instruction to print the AWS_REGION GitHub secret, which was already present in the repository. I expected to see the value displayed in the workflow logs after the action was executed successfully. I then submitted a pull request to the main branch with these changes, and as expected, the modified workflow was triggered and executed successfully, even though the pull request had not been reviewed, approved, or merged! Interesting. As seen in the screenshot above, the workflows triggered by my pull request were executed successfully. You might notice there are two workflow runs displayed, which I will address in the next section. For now, let's focus on the workflow labeled "test: modified GitHub workflows" at the bottom. Once the workflow was completed, I reviewed the logs, and as expected, the AWS_REGION GitHub secret was masked, as shown in the following image. This outcome was anticipated, as I had previously encountered a similar article detailing this kind of exploit, which informed my approach to this experiment. Now, if the secrets were concealed, how did the attacker manage to access them? This question led to my second key finding: 2. GitHub secrets can be exposed by making curl requests to third-party APIs within a modified workflow Yeah, you read that right! To test this, I further edited the workflow to include a request to a RequestBin I created on Pipedream. The screenshot below illustrates the updated workflow. This explains the second workflow run shown in the earlier screenshot, confirming that both workflows were executed successfully. On Pipedream's RequestBin, I was able to view the GitHub "secret" in plain text. This raised a concerning question: could anyone simply submit a pull request to an open-source project and easily access sensitive keys? Securing Your Workflows Given the potential vulnerabilities uncovered during this experiment, it’s crucial to understand how to secure GitHub workflows to prevent unauthorized access to sensitive data. GitHub provides several settings that can be configured to reduce the risk of exploitation: Actions permissions setting:
By default, all actions are permitted to run, regardless of the author. For enhanced security, this setting should be updated to limit permissions, ensuring that only trusted workflows can execute.


Fork pull-request workflows from outside collaborators setting:
This setting defines which outside collaborators require approval to run workflows in pull requests. Properly configuring this setting is critical, as misconfiguration could expose your repository to potential exploits. Additionally, GitHub’s documentation notes that workflows triggered from forks do not have access to sensitive data like secrets. This emphasizes the importance of reviewing the settings for repositories where sensitive data is handled. By implementing these security measures, repositories can significantly reduce the likelihood of similar vulnerabilities being exploited. Possible Explanations for the Exploit Taking all of the above factors into consideration, if the rumors are accurate and Ledger's NPM secrets were indeed compromised, a few scenarios might explain how this occurred: CASE #1: The package maintainers overlooked the configuration settings and allowed the compromised workflows to run.
CASE #2: The attacker somehow obtained full write access to the repository.
CASE #3: The attacker is, or was, a previous contributor to the project.
CASE #4: The exploit was carried out as an inside job. My Analysis Upon reviewing these scenarios, I believe that CASE #3 is the most plausible explanation. A previous contributor may not need explicit approval to trigger workflows in the repository, making it easier to exploit this vulnerability. I have seen various discussions on social media suggesting that a former employee’s account might have been compromised, which would support CASE #3. However, until an official statement is released by Ledger, the exact cause remains speculative. Final Thoughts Through this experiment, I gained a deeper understanding of how workflow vulnerabilities can be exploited and how developers can protect their repositories from such threats. By implementing the recommended security settings and thoroughly reviewing contributor permissions, open-source maintainers can minimize the risk of unauthorized access. In December 2023, it was discovered that an NPM package commonly used by decentralized web applications (dApps) had been compromised. The package in question, @ledgerhq/connect-kit , is maintained by Ledger, a well-known and arguably the most trusted provider of secure hardware wallets. Ironic right? @ledgerhq/connect-kit Well, not really, because the compromised package has nothing to do with the ledger's secure hardware wallets. However, the incident understandably raised concerns among users about the security of their assets, despite those assets being stored offline in hardware wallets. While the compromised package posed no immediate threat to Ledger's hardware devices, the situation sparked widespread discussion and speculation. The prevailing theory suggests that the compromise occurred due to a vulnerability in Ledger’s GitHub workflow. It is believed that an attacker exploited a GitHub pull request workflow to gain access to Ledger's NPM keys, enabling them to publish malicious code. The malicious update reportedly caused a secondary window to open when users attempted to connect their wallets. The Experiment The Experiment The incident piqued my curiosity, prompting me to question whether GitHub workflows were inherently flawed or if there was more nuance to the exploit. To explore this, I conducted an experiment to see if I could replicate the vulnerability. Using an existing open-source repository, I attempted to recreate the exploit. During my testing, I discovered that: 1. A pull request can edit a workflow and the new workflow will run immediately after the pull request is made 1. A pull request can edit a workflow and the new workflow will run immediately after the pull request is made The screenshot below displays the contents of a pipeline.yml file from the repository I was working with. The pipeline is configured to trigger every push to the main branch, deploying the serverless application to AWS . pipeline.yml AWS I proceeded by creating a new branch within the repository and modifying the pipeline file. The updated configuration was set to trigger the workflow on every pull request, regardless of the branch. The screenshot below illustrates the modified state of the file. Along with these modifications, I added an instruction to print the AWS_REGION GitHub secret, which was already present in the repository. I expected to see the value displayed in the workflow logs after the action was executed successfully. AWS_REGION I then submitted a pull request to the main branch with these changes, and as expected, the modified workflow was triggered and executed successfully, even though the pull request had not been reviewed, approved, or merged! Interesting. As seen in the screenshot above, the workflows triggered by my pull request were executed successfully. You might notice there are two workflow runs displayed, which I will address in the next section. For now, let's focus on the workflow labeled "test: modified GitHub workflows" at the bottom. Once the workflow was completed, I reviewed the logs, and as expected, the AWS_REGION GitHub secret was masked, as shown in the following image. This outcome was anticipated, as I had previously encountered a similar article detailing this kind of exploit, which informed my approach to this experiment. AWS_REGION Now, if the secrets were concealed, how did the attacker manage to access them? This question led to my second key finding: 2. GitHub secrets can be exposed by making curl requests to third-party APIs within a modified workflow 2. GitHub secrets can be exposed by making requests to third-party APIs within a modified workflow Yeah, you read that right! To test this, I further edited the workflow to include a request to a RequestBin I created on Pipedream . The screenshot below illustrates the updated workflow. Pipedream This explains the second workflow run shown in the earlier screenshot, confirming that both workflows were executed successfully. On Pipedream's RequestBin, I was able to view the GitHub "secret" in plain text. This raised a concerning question: could anyone simply submit a pull request to an open-source project and easily access sensitive keys? Securing Your Workflows Securing Your Workflows Given the potential vulnerabilities uncovered during this experiment, it’s crucial to understand how to secure GitHub workflows to prevent unauthorized access to sensitive data. GitHub provides several settings that can be configured to reduce the risk of exploitation: GitHub Actions permissions setting:
By default, all actions are permitted to run, regardless of the author. For enhanced security, this setting should be updated to limit permissions, ensuring that only trusted workflows can execute. Fork pull-request workflows from outside collaborators setting:
This setting defines which outside collaborators require approval to run workflows in pull requests. Properly configuring this setting is critical, as misconfiguration could expose your repository to potential exploits. Actions permissions setting: By default, all actions are permitted to run, regardless of the author. For enhanced security, this setting should be updated to limit permissions, ensuring that only trusted workflows can execute. Actions permissions setting: Actions permissions setting: By default, all actions are permitted to run, regardless of the author. For enhanced security, this setting should be updated to limit permissions, ensuring that only trusted workflows can execute. Fork pull-request workflows from outside collaborators setting: This setting defines which outside collaborators require approval to run workflows in pull requests. Properly configuring this setting is critical, as misconfiguration could expose your repository to potential exploits. Fork pull-request workflows from outside collaborators setting: Fork pull-request workflows from outside collaborators setting: This setting defines which outside collaborators require approval to run workflows in pull requests. Properly configuring this setting is critical, as misconfiguration could expose your repository to potential exploits. Additionally, GitHub’s documentation notes that workflows triggered from forks do not have access to sensitive data like secrets. This emphasizes the importance of reviewing the settings for repositories where sensitive data is handled. By implementing these security measures, repositories can significantly reduce the likelihood of similar vulnerabilities being exploited. Possible Explanations for the Exploit Possible Explanations for the Exploit Taking all of the above factors into consideration, if the rumors are accurate and Ledger's NPM secrets were indeed compromised, a few scenarios might explain how this occurred: CASE #1: The package maintainers overlooked the configuration settings and allowed the compromised workflows to run. CASE #2: The attacker somehow obtained full write access to the repository. CASE #3: The attacker is, or was, a previous contributor to the project. CASE #4: The exploit was carried out as an inside job. CASE #1: The package maintainers overlooked the configuration settings and allowed the compromised workflows to run. CASE #1: CASE #2: The attacker somehow obtained full write access to the repository. CASE #2: CASE #3 : The attacker is, or was, a previous contributor to the project. CASE #3 CASE #4: The exploit was carried out as an inside job. CASE #4: My Analysis My Analysis Upon reviewing these scenarios, I believe that CASE #3 is the most plausible explanation. A previous contributor may not need explicit approval to trigger workflows in the repository, making it easier to exploit this vulnerability. I have seen various discussions on social media suggesting that a former employee’s account might have been compromised, which would support CASE #3. However, until an official statement is released by Ledger, the exact cause remains speculative. Final Thoughts Final Thoughts Through this experiment, I gained a deeper understanding of how workflow vulnerabilities can be exploited and how developers can protect their repositories from such threats. By implementing the recommended security settings and thoroughly reviewing contributor permissions, open-source maintainers can minimize the risk of unauthorized access.

How a Compromised NPM Package Revealed GitHub Workflow Vulnerabilities

In the modern age of development, having an efficient developer workflow plays a huge role in shipping quality software as fast as possible. Open source is a valuable resource with tons of projects that are supported by the community and allows us to better tailor the solutions for our particular needs. In this article, I decided to manually handpick 16 of my favorite open-source projects that can boost your development workflow and allow you to save time. From testing environments, and auth solutions to robust analytics, database managers, and deployment solutions, I hope that these tools will improve your craft. I also added direct links, descriptions, and previews of each project so that you can get an idea about them right away while reading the article. 1. Firecamp Firecamp is a cross-platform API development tool. It puts REST, GraphQL, and WebSocket API testing into one interface. This allows you to test and debug in a single application, reducing wasted time on context switches between different tools. 2. Budibase Budibase is an open-source, low-code platform for building powerful and effective internal tools and business apps. It enables rapid application development, reduces manual coding, and can be integrated with many popular databases/services. 3. Hanko Hanko is an open-source auth solution for creating passwordless logins with passkeys and passcodes. It produces a secure yet easy-to-implement system for authentication, reducing complexity and time spent managing user authentications. 4. Cerbos Cerbos is a policy-based access control system that makes it easy for developers to manage user permissions. It decouples the access control logic from the application code, which provides flexibility in managing authorization rules. 5. Primo Primo is a visual CMS for static sites that allows developers to edit the content of the sites you are building on the go. It is also integrated with an intuitive visual editor to give the best developer experience with an instant preview. 6. Typebot Typebot is a platform to create chatbots in a no-code interface. You can further embed them anywhere on your web/mobile apps, and collect results in real-time to help in user support. 7. Mermaid Mermaid is a diagramming tool using JavaScript that takes the textual definition of diagrams and charts and draws them. It allows users to visually create flowcharts, sequence diagrams, and classes, among others, in a dynamic way in either a browser or markdown files. 8. Flipt Flipt is an enterprise-ready, GitOps-enabled, CloudNative system for managing the feature roadmap of your applications. It allows gradual rollout, A/B testing, and experimentation to follow DevOps best practices and separate releases from deployments. 9. SigNoz SigNoz is a free-to-use observability platform with out-of-the-box metrics, logs, and traces for troubleshooting. This provides an easy-to-use interface and detailed overview for real-time diagnosis of performance issues and application optimization. 10. Plausible Plausible Analytics is an open-source web analytics tool that extensively focuses on privacy and is considered easier to use than Google Analytics. It provides clear and actionable insights without unnecessary bloat and clutter, making it easier for the developers to monitor performance on the website. 11. Supabase Supabase is an open-source alternative to Firebase. It can also serve as a backend-as-a-service, providing real-time databases, authentication, and storage. It allows developers to quickly develop and scale their applications with minimal setup while utilizing tools they already know. 12. Prisma Prisma is an open-source object-relational mapping tool that provides easier database access for Node.js and TypeScript applications. It provides type-safe database queries, automated migrations, and a rich data model, leading to more efficient and error-free database management. 13. Beekeeper Beekeeper Studio is a modern, open-source SQL editor and DB manager. It provides an interface to write queries, manage the databases, and visualize your data for MySQL, Postgres, SQLite, SQL Server, and more. 14. Coolify Coolify is an open-source, self-hosted Heroku / Netlify / Vercel alternative for the deployment and management of web apps and databases. It helps you manage your servers, applications, and databases on your own hardware; you only need an SSH connection. 15. Jest Jest is a fast and safe JavaScript testing framework with a focus on simplicity. It comes with an easy-to-use test environment with lots of features to enhance performance, like snapshot testing or parallelization. 16. Oh My Zsh Oh My Zsh is a community-driven framework for managing your Zsh configuration. It is equipped with a number of helpful plugins and themes, which extend the terminal with customizability with little effort. Did you like the resources? Here is more 👇 Join 6000+ others to receive the best DEV resources, tools, productivity tips, and career growth advice I discover by subscribing to my newsletter! Also, connect with me on Twitter, LinkedIn, and GitHub! Writing has always been my passion and it gives me pleasure to help and inspire people. If you want to get featured or partner up, feel free to get in touch! In the modern age of development, having an efficient developer workflow plays a huge role in shipping quality software as fast as possible. Open source is a valuable resource with tons of projects that are supported by the community and allows us to better tailor the solutions for our particular needs. In this article, I decided to manually handpick 16 of my favorite open-source projects that can boost your development workflow and allow you to save time. From testing environments, and auth solutions to robust analytics, database managers, and deployment solutions, I hope that these tools will improve your craft. I also added direct links, descriptions, and previews of each project so that you can get an idea about them right away while reading the article. 1. Firecamp Firecamp Firecamp is a cross-platform API development tool. It puts REST, GraphQL, and WebSocket API testing into one interface. This allows you to test and debug in a single application, reducing wasted time on context switches between different tools. 2. Budibase Budibase Budibase is an open-source, low-code platform for building powerful and effective internal tools and business apps. It enables rapid application development, reduces manual coding, and can be integrated with many popular databases/services. 3. Hanko Hanko Hanko is an open-source auth solution for creating passwordless logins with passkeys and passcodes. It produces a secure yet easy-to-implement system for authentication, reducing complexity and time spent managing user authentications. 4. Cerbos Cerbos Cerbos is a policy-based access control system that makes it easy for developers to manage user permissions. It decouples the access control logic from the application code, which provides flexibility in managing authorization rules. 5. Primo Primo Primo is a visual CMS for static sites that allows developers to edit the content of the sites you are building on the go. It is also integrated with an intuitive visual editor to give the best developer experience with an instant preview. 6. Typebot Typebot Typebot is a platform to create chatbots in a no-code interface. You can further embed them anywhere on your web/mobile apps, and collect results in real-time to help in user support. 7. Mermaid Mermaid Mermaid is a diagramming tool using JavaScript that takes the textual definition of diagrams and charts and draws them. It allows users to visually create flowcharts, sequence diagrams, and classes, among others, in a dynamic way in either a browser or markdown files. 8. Flipt Flipt Flipt is an enterprise-ready, GitOps-enabled, CloudNative system for managing the feature roadmap of your applications. It allows gradual rollout, A/B testing, and experimentation to follow DevOps best practices and separate releases from deployments. 9. SigNoz SigNoz SigNoz is a free-to-use observability platform with out-of-the-box metrics, logs, and traces for troubleshooting. This provides an easy-to-use interface and detailed overview for real-time diagnosis of performance issues and application optimization. 10. Plausible Plausible Plausible Analytics is an open-source web analytics tool that extensively focuses on privacy and is considered easier to use than Google Analytics. It provides clear and actionable insights without unnecessary bloat and clutter, making it easier for the developers to monitor performance on the website. 11. Supabase Supabase Supabase is an open-source alternative to Firebase. It can also serve as a backend-as-a-service, providing real-time databases, authentication, and storage. It allows developers to quickly develop and scale their applications with minimal setup while utilizing tools they already know. 12. Prisma Prisma Prisma is an open-source object-relational mapping tool that provides easier database access for Node.js and TypeScript applications. It provides type-safe database queries, automated migrations, and a rich data model, leading to more efficient and error-free database management. 13. Beekeeper Beekeeper Beekeeper Studio is a modern, open-source SQL editor and DB manager. It provides an interface to write queries, manage the databases, and visualize your data for MySQL, Postgres, SQLite, SQL Server, and more. 14. Coolify Coolify Coolify is an open-source, self-hosted Heroku / Netlify / Vercel alternative for the deployment and management of web apps and databases. It helps you manage your servers, applications, and databases on your own hardware; you only need an SSH connection. 15. Jest Jest Jest is a fast and safe JavaScript testing framework with a focus on simplicity. It comes with an easy-to-use test environment with lots of features to enhance performance, like snapshot testing or parallelization. 16. Oh My Zsh Oh My Zsh Oh My Zsh is a community-driven framework for managing your Zsh configuration. It is equipped with a number of helpful plugins and themes, which extend the terminal with customizability with little effort. Did you like the resources? Here is more 👇 Did you like the resources? Here is more 👇 Join 6000+ others to receive the best DEV resources, tools, productivity tips, and career growth advice I discover by subscribing to my newsletter ! my newsletter my newsletter Also, connect with me on Twitter , LinkedIn , and GitHub ! Twitter Twitter LinkedIn LinkedIn GitHub GitHub Writing has always been my passion and it gives me pleasure to help and inspire people. If you want to get featured or partner up, feel free to get in touch ! get in touch get in touch

16 Handpicked Open-Source Projects to Improve Your Developer Workflow

In this post, I go through how I have set up my Obsidian and Hugo blogging workflow. I use a single vault and auto-publish my articles with hotkeys. If you clicked on this article, you probably know what Obsidian and Hugo are, but if you don’t, here’s a quick explanation: Obsidian Obsidian is a feature-packed markdown editor. But it’s not just a markdown editor. It’s a way to manage knowledge. It’s great for organizing your thoughts in a flexible, non-linear way. Obsidian works on all platforms. So, you can write articles from basically any platform. I have been taking all of my notes in it for a couple of months now, and it’s amazing! Hugo Hugo is an ultra-fast static website generator made in Golang. I have been using Hugo for my blog for almost 2 years now. I recently switched the theme of my blog. Read more about the change New Look, new start. Using Obsidian with Hugo In this guide, I’ll show you how to get Obsidian and Hugo working together. I won’t cover the initial setup of either tool, but I’ll explain how to integrate them for a smooth blogging workflow. If you need help setting up Hugo, check out my guide: How I Setup This Blog for Free (Domain, Hosting, SSL) Complete Guide. And if you’re new to Obsidian, check out this Getting Started Guide. Goals for Using Hugo With Obsidian My goals for the setup are: Using a single obsidian vault.
Have an easy-to-use obsidian template that I can use for my blog posts.
Keep my personal vault folders private.
Auto-publish using obsidian hotkeys.
Have all markdown files in a public GitHub repository, so that people can propose changes Existing Setup Here’s how my current workflow with Obsidian and Hugo looks: I write and edit articles directly in Obsidian, within the content folder of my Hugo project.


I run the Hugo command to generate the static site.


I push the changes to GitHub.


Render.com automatically picks up the changes and deploys the updated site. Journey If you want to skip the journey part, you can go straight to The Sauce. I will be going through a couple of mistakes that I made while setting this up. Mistake #1 The first idea that I had was to create a simple symlink (I use Linux btw) that would link the two folders together. Basically, I have two folders: blog/
vault/ The blog folder contains all the blog folders, and the vault is my personal vault. The symlink would link these folders. blog/content
vault/Blog However, the problem with a symlink is that the folder content is not visible in my git repo. This means that people can not propose changes to any of my articles. Mistake #2 I wanted to have my folders synced. I tried writing a couple of bash scripts that automatically synced the two folders using a cronjob. However, having that constantly running in the background is a waste of resources when I am not writing. Simply running the scripts via CLI is just not that smooth. The Sauce Basically, the way that I have set this up is I have two folders: blog
vault The blog folder contains all the necessary Hugo files and also has a sub-directory called content that houses all of the markdown blog files. I created a new folder inside my vault called Blog. blog/content
vault/Blog After that, I copied all of my files from the content directory to the Blog. I then started writing this very article. Obsidian Templates I needed some way to set up a simple obsidian template to contain all of the required hugo front matter. That is quite easy. Read about how to set templates Templates - obsidian.md I created a file called Blog Post in my templates folder. My Blog Post template contains the following: ---
title: "{{Title}}"
description: 
date: "{{date:YYYY-MM-DD}}T{{time:HH:mm:ss}}+00:00"
draft: true
---


**If you enjoyed this article consider [supporting me](https://4rkal.com/donate)** I have all the required front matter including a title, description, and a date in the format that Hugo asks. I also added a small donation text that I include at the bottom of every article. This means that I can automatically insert this template into any file and start writing! Folder Syncing Now, I want all of my files in my vault/Blog directory to be copied over to the blog/content. Essentially connecting Hugo and Obsidian. Thanks to a helpful Discord user, I found the obsidian-shellcommands plugin. NOTE: This plugin does not currently work very well with the flatpak version of Obsidian (since flatpak isolates the environment). Using another alternative (.deb or appimage) seems to work. It allows you to run shell commands in the background with a hotkey. The steps to set this up are the following: Install the plugin
Enable the plugin
Go to the plugin options
Click on New shell command
Now, you will need to enter a shell command to copy the files from one folder to the other. On Linux/MacOS, that is: cp -a ~/folder1/. ~/folder2/ In my case, that is cp -a ~/Documents/vault/Blog/. ~/Documents/blog/content/ On Windows, it most probably is: robocopy "%USERPROFILE%\folder1" "%USERPROFILE%\folder2" /E /COPYALL After that, we need to set a hotkey that will run the command. Click on the (+) icon to go to the hotkey settings and assign a hotkey. My hotkey is CTR + 0, simply because that was available. Now, every time that I run the hotkey it copies all of my files to the Hugo folder ready to be published. Auto-Publishing Scripts I also want to be able to automatically publish my articles. But I want it to happen when hitting a hotkey. I wrote a small script that does exactly that: #!/bin/bash
cd ~/Documents/blog

hugo

git add .
git commit -m "new"
git push -u origin main This script will build my website, commit it, and push it to my GitHub repo, where it is picked up and published. Read How I set up this blog for free (domain, hosting, ssl) Complete Guide to learn how to set up your own blog for free. Don’t forget to make the script executable by running. chmod +x ./YOURSCRIPT.sh Then create a new shell command for the shellcommand plugin (as we did before) and enter the path to your script. In my case, that is: ~/Documents/blog/push.sh Then enter a hotkey, and you’re done! Conclusion I can now simply open my obsidian vault, create a new file, insert my template, and have all the info automatically entered. I then write my article inside of obsidian. Run my hotkey and copy all the files into the Hugo directory. Hit another key, and my blog is published! If you enjoyed this article consider supporting me. Subscribe: Subscribe to my free newsletter: https://newsletter.4rkal.com/subscription/form In this post, I go through how I have set up my Obsidian and Hugo blogging workflow. I use a single vault and auto-publish my articles with hotkeys. If you clicked on this article, you probably know what Obsidian and Hugo are, but if you don’t, here’s a quick explanation: Obsidian Obsidian is a feature-packed markdown editor. But it’s not just a markdown editor. It’s a way to manage knowledge. It’s great for organizing your thoughts in a flexible, non-linear way. Obsidian Obsidian works on all platforms. So, you can write articles from basically any platform. I have been taking all of my notes in it for a couple of months now, and it’s amazing! Hugo Hugo is an ultra-fast static website generator made in Golang. I have been using Hugo for my blog for almost 2 years now. I recently switched the theme of my blog. Read more about the change New Look, new start . Hugo New Look, new start Using Obsidian with Hugo In this guide, I’ll show you how to get Obsidian and Hugo working together. I won’t cover the initial setup of either tool, but I’ll explain how to integrate them for a smooth blogging workflow. If you need help setting up Hugo, check out my guide: How I Setup This Blog for Free (Domain, Hosting, SSL) Complete Guide . And if you’re new to Obsidian, check out this Getting Started Guide . How I Setup This Blog for Free (Domain, Hosting, SSL) Complete Guide Getting Started Guide Goals for Using Hugo With Obsidian My goals for the setup are: Using a single obsidian vault. Have an easy-to-use obsidian template that I can use for my blog posts. Keep my personal vault folders private. Auto-publish using obsidian hotkeys. Have all markdown files in a public GitHub repository, so that people can propose changes Using a single obsidian vault . obsidian vault Have an easy-to-use obsidian template that I can use for my blog posts. obsidian template Keep my personal vault folders private. Auto-publish using obsidian hotkeys. Have all markdown files in a public GitHub repository , so that people can propose changes public GitHub repository Existing Setup Here’s how my current workflow with Obsidian and Hugo looks: I write and edit articles directly in Obsidian, within the content folder of my Hugo project. I run the Hugo command to generate the static site. I push the changes to GitHub. Render.com automatically picks up the changes and deploys the updated site. I write and edit articles directly in Obsidian, within the content folder of my Hugo project. I write and edit articles directly in Obsidian, within the content folder of my Hugo project. content I run the Hugo command to generate the static site. I run the Hugo command to generate the static site. I push the changes to GitHub. I push the changes to GitHub. Render.com automatically picks up the changes and deploys the updated site. Render.com automatically picks up the changes and deploys the updated site. Render.com Journey If you want to skip the journey part, you can go straight to The Sauce. If you want to skip the journey part, you can go straight to The Sauce . The Sauce I will be going through a couple of mistakes that I made while setting this up. Mistake #1 The first idea that I had was to create a simple symlink (I use Linux btw) that would link the two folders together. Basically, I have two folders: blog/
vault/ blog/
vault/ The blog folder contains all the blog folders, and the vault is my personal vault. The symlink would link these folders. blog/content
vault/Blog blog/content
vault/Blog However, the problem with a symlink is that the folder content is not visible in my git repo. This means that people can not propose changes to any of my articles. the problem Mistake #2 I wanted to have my folders synced. I tried writing a couple of bash scripts that automatically synced the two folders using a cronjob. However, having that constantly running in the background is a waste of resources when I am not writing. Simply running the scripts via CLI is just not that smooth. The Sauce Basically, the way that I have set this up is I have two folders: blog
vault blog
vault The blog folder contains all the necessary Hugo files and also has a sub-directory called content that houses all of the markdown blog files. I created a new folder inside my vault called Blog. blog/content
vault/Blog blog/content
vault/Blog After that, I copied all of my files from the content directory to the Blog. I then started writing this very article. I then started writing this very article. Obsidian Templates I needed some way to set up a simple obsidian template to contain all of the required hugo front matter. That is quite easy. Read about how to set templates Templates - obsidian.md Templates - obsidian.md I created a file called Blog Post in my templates folder. Blog Post My Blog Post template contains the following: Blog Post ---
title: "{{Title}}"
description: 
date: "{{date:YYYY-MM-DD}}T{{time:HH:mm:ss}}+00:00"
draft: true
---


**If you enjoyed this article consider [supporting me](https://4rkal.com/donate)** ---
title: "{{Title}}"
description: 
date: "{{date:YYYY-MM-DD}}T{{time:HH:mm:ss}}+00:00"
draft: true
---


**If you enjoyed this article consider [supporting me](https://4rkal.com/donate)** I have all the required front matter including a title, description, and a date in the format that Hugo asks. I also added a small donation text that I include at the bottom of every article. This means that I can automatically insert this template into any file and start writing! Folder Syncing Now, I want all of my files in my vault/Blog directory to be copied over to the blog/content. Essentially connecting Hugo and Obsidian. Thanks to a helpful Discord user, I found the obsidian-shellcommands plugin. obsidian-shellcommands NOTE: This plugin does not currently work very well with the flatpak version of Obsidian (since flatpak isolates the environment). Using another alternative (.deb or appimage) seems to work. NOTE: It allows you to run shell commands in the background with a hotkey. The steps to set this up are the following: Install the plugin Enable the plugin Go to the plugin options Click on New shell command Now, you will need to enter a shell command to copy the files from one folder to the other. Install the plugin Install the plugin Enable the plugin Go to the plugin options Click on New shell command New shell command Now, you will need to enter a shell command to copy the files from one folder to the other. On Linux/MacOS, that is: cp -a ~/folder1/. ~/folder2/ cp -a ~/folder1/. ~/folder2/ In my case, that is cp -a ~/Documents/vault/Blog/. ~/Documents/blog/content/ cp -a ~/Documents/vault/Blog/. ~/Documents/blog/content/ On Windows, it most probably is: robocopy "%USERPROFILE%\folder1" "%USERPROFILE%\folder2" /E /COPYALL robocopy "%USERPROFILE%\folder1" "%USERPROFILE%\folder2" /E /COPYALL After that, we need to set a hotkey that will run the command. Click on the (+) icon to go to the hotkey settings and assign a hotkey. My hotkey is CTR + 0 , simply because that was available. CTR + 0 Now, every time that I run the hotkey it copies all of my files to the Hugo folder ready to be published. Auto-Publishing Scripts I also want to be able to automatically publish my articles. But I want it to happen when hitting a hotkey. I wrote a small script that does exactly that: #!/bin/bash
cd ~/Documents/blog

hugo

git add .
git commit -m "new"
git push -u origin main #!/bin/bash
cd ~/Documents/blog

hugo

git add .
git commit -m "new"
git push -u origin main This script will build my website, commit it, and push it to my GitHub repo, where it is picked up and published. Read How I set up this blog for free (domain, hosting, ssl) Complete Guide to learn how to set up your own blog for free. How I set up this blog for free (domain, hosting, ssl) Complete Guide Don’t forget to make the script executable by running. chmod +x ./YOURSCRIPT.sh chmod +x ./YOURSCRIPT.sh Then create a new shell command for the shellcommand plugin (as we did before) and enter the path to your script. In my case, that is: ~/Documents/blog/push.sh ~/Documents/blog/push.sh Then enter a hotkey, and you’re done! Conclusion I can now simply open my obsidian vault, create a new file, insert my template, and have all the info automatically entered. I then write my article inside of obsidian. Run my hotkey and copy all the files into the Hugo directory. Hit another key, and my blog is published! If you enjoyed this article consider supporting me. If you enjoyed this article consider supporting me . supporting me Subscribe: Subscribe to my free newsletter: https://newsletter.4rkal.com/subscription/form https://newsletter.4rkal.com/subscription/form

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